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When targeting embedded applications such as on-board visual localization for small Unmanned Air Vehicles (UAV), available hardware generally becomes a limiting factor. For this reason, the usual strategy is to rely on pure motion integration and/or restricting the size of the map, i.e. performing visual odometry. Moreover, if monocular vision is employed, due to the additional computational cost...
Visual or image-based self-localization refers to the recovery of a camera's position and orientation in the world based on the images it records. In this paper, we deal with the problem of self-localization using a sequence of images. This application is of interest in settings where GPS-based systems are unavailable or imprecise, such as indoors or in dense cities. Unlike typical approaches, we...
The present paper describes a dual approach using pseudo-3D vision for Machine-Awareness in indoor environment. Provided by color and depth cameras of the a Kinect system, the aforementioned duality presents an appealing solution for robots' 3D-vision. Placing the human-robot and in a more general way the human-machine interactions as a key outcome of the expected visual Machine-Awareness, the proposed...
In conventional visual odometry (VO) systems, perspective-n-point (PnP) method and random sample consensus (RANSAC) algorithm are generally used to estimate camera poses. However, heavy computational burden is incurred, and the pose estimations are not reliable as well. Therefore, in this paper, an improved VO system is proposed, where an off-line camera calibration method is used to obtain lesser...
Unsupervised segmentation of action segments in egocentric videos is a desirable feature in tasks such as activity recognition and content-based video retrieval. Reducing the search space into a finite set of action segments facilitates a faster and less noisy matching. However, there exist a substantial gap in machine's understanding of natural temporal cuts during a continuous human activity. This...
In this paper we describe a recursive filter for the fusion of inertial and visual measurements for self-positioning, where the sensors are attached rigidly to the moving person or object. The system is self-contained, requires no infrastructure and is suitable for both indoor and seamless indoor/outdoor localization. The suggested approach fuses the images acquired by a stereo camera with a 3-axis...
Visual Simultaneous Localization and Mapping (VSLAM) requires feature detection on visual data. In indoor scenes that include architectures such as plain walls and doors, there are no or less corners detected, in such cases tracking will be lost. To overcome this situation we track different types of features that help in feature extraction even in textureless scenes. Line features are used to get...
Visual Simultaneous Localization and Mapping (SLAM) has been used for markerless tracking in augmented reality applications. Distributed SLAM helps multiple agents to collaboratively explore and build a global map of the environment while estimating their locations in it. One of the main challenges in Distributed SLAM is to identify local map overlaps of these agents, especially when their initial...
Reliable localization is one of the most important parts of an MAV system. Localization in an indoor GPS-denied environment is a relatively difficult problem. Current vision based algorithms track optical features to calculate odometry. We present a novel localization method which can be applied in an environment having orthogonal sets of equally spaced lines to form a grid. With the help of a monocular...
This paper sets out and presents a new approach to determine the stroke volume of the artificial ventricle. The stroke volume of the chamber is one of the basic heart function parameters. For the artificial heart assist purpose, in the study this value is calculated based on the mapped shape of the flaccid membrane of the extracorporeal pneumatic heart assist pump. This is a continuation of the earlier...
This paper investigates dynamic visual feedback position tracking of two kinds of two-wheeled vehicles with a camera or a target object for visual measurements. A problem formulation is first provided, where the dynamics of the camera vehicle is explicitly considered and the target vehicle velocity is expressed by a Fourier series expansion. Next, passivity-based tracking control structure is explained...
Long-term place recognition for vehicles or robots in outdoor environment is still a tackling issue: numerous changes occur in appearance due to illumination variations or weather phenomena for instance, when using visual sensors. Few methods from the literature try to manage different visual sources while it could favor data interoperability across variable sensors. In this paper, we emphasis our...
Use of surveillance cameras as a monitoring tool for home environments, elderly, and children has becoming a common practice. However, people with visual impairments have difficulties in using this kind of device because it relies only on visual information. Towards solving this problem, this work aims to propose a solution that combines deep learning techniques for object recognition in the video...
We propose an active visual tracker with collision avoidance for camera-equipped robots in dense multi-agent scenarios. The objective of each tracking agent (robot) is to maintain visual fixation on its moving target while updating its velocity to avoid other agents. However, when multiple robots are present or targets intensively intersect each other, robots may have no accessible collision-avoiding...
Using machines to save manpower has always been the core concept of technological development. For some time, the process of replacing the brain has made great progress in the development of decision-making, such as identification, and has made a wide range of applications. The self-driving car as the representative of the intelligent robot has become a hot topic. Based on the scene of the use of...
In this paper, we propose a new method that can reconstruct the more accurate 3D surface point clouds from the standard laparoscopic (single camera) imaging system even with less sequential (less overlapped) and low quality images, which is a promising way to achieve a faster surgical guidance. The strength of our method is to find more accurate feature points that lead to precise 3D reconstruction...
Eyes are organs of our visual system. In this paper, we are presenting a unique intelligent electronic eye that provides road guidance to blind people while they are walking. Surrounding visual data is collected by image and obstacle sensors mounted on a helmet which the user has to put in. The data is sent to a processor which works in a line similar to our brain function. The processor analyses...
Rather than being completely isolated, the various human sensory systems can influence each other, sometimes strongly. For example, the cognitive phenomenon known as “colored hearing” involves seeing colors in response to auditory stimuli. This type of special cognitive condition, in which one sensory stimulus evokes a different perception from that of the trigger, is known as “synesthesia.” Previous...
In this paper we propose a neural network allowing a mobile robot to learn artwork appreciation. The learning is based on the social referencing approach. The robot acquires its knowledge (artificial taste) from the interaction with humans. We present and analyze specifically the visual system, its impact on the robot behavior, and at the end, we analyze the readability of our robot behavior according...
One of the greatest technological improvements in recent years is the rapid progress using machine learning for processing visual data. Among all factors that contribute to this development, datasets with labels play crucial roles. Several datasets are widely reused for investigating and analyzing different solutions in machine learning. Many systems, such as autonomous vehicles, rely on components...
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